Processed Food Traceability using Blockchain Technology

The system design for the supply chain of processed foods that makes use of the advantages of blockchain technology. This research emphasises on critical supply chain management for the success of many sectors and importance of protecting the visibility of the overall process. The suggested system design creates a multimode storage management that offers increased visibility, safety, and productivity in the supply chain for processed foods by combining the strengths of both traditional storage and blockchain storage. There are various benefits to using blockchain-based in the supply chain for packaged foods. It ensures the transparency of the entire process and removes the need of middlemen, lowering the danger of fraud or manipulation. Additionally, blockchain technology's ability to track food goods accurately from the farm to the customer makes it simpler to identify the source of food products in the event of a food safety concern. In addition to shielding consumers from potential health risks, this also preserves the industry's good name. Blockchain transactions' automatic and secure replaces with traditional human procedures, speed up transaction processing, and shorten the time it takes for food products to get to consumers. As a result, consumers may be more satisfied and food suppliers and manufacturers may incur cheaper expenses. In order to enhance the supply chain for processed foods, this system suggests a system architecture that combines the advantages of blockchain technology and machine learning models. Using linear regression with Lasso and a 0.2 test split, the machine learning algorithm achieved an Accuracy Rate of 0.79 and a Testing Accuracy of 0.84. Onion, sesame, peanut, mustard, and corn are the top 5 most in-demand crops, and the model gives the farmer entity recommendations for crop output based on anticipated demand. The supply chain for processed foods may become more effective and transparent thanks to the proposed approach.